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Anton Dahlberg
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Biochemistry 201 Advanced Molecular Biology (http://cmgm cmgm.stanford.

1 Biochemistry 201 Advanced Molecular Biology ( cmgm.stanford.edu/biochem201/) Bioinformatics: Discovering Function from Sequence Doug Brutlag Departments of Biochemistry June 4, 1999

2 Discovering Function from Protein Sequence BLOCK, Weight Matrix or Position Specific Scoring Matrix Position A R N D C Q E G H I L K M F P S T W Y V Consensus Sequences Zinc Finger (C2H2 type) C.{2,4} C.{12} H.{3,5} H Sequences of Common Structure or Function Sequence Alignments VLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHF------DLSHGS : : : : : : : : : : : 2 HLTPEEKSAVTALWGKV--NVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGN AA1 Profiles, PSI-BLAST Hidden Markov Models D 2 I 1 I 2 I 3 I 4 I 5 AA2 D 3 AA3 D 4 AA4 D 5 AA5 AA6

3 Sequence Alignment Problem T C A T G C A T T G

4 Sequence Alignment Problem T C A T G C A T T G

5 Sequence Alignment Problem T C A T G C A T T G T C A T G C A T T G

6 Sequence Alignment (exact) X X F--SGGNTHIYMNHVEQCKEILRREPKELCELVISGLPYKFRYLSTKE-QLK-Y GDFIHTLGDAHIYLNHIEPLKIQLQREPRPFPKLRILRKVEKIDDFKAEDFQIEGYN X X

7 Needleman-Wunsch Algorithm (1)

8 Needleman-Wunsch Algorithm (2)

9 Needleman-Wunsch Algorithm (3)

10 Needleman-Wunsch Algorithm (4)

11 Sequence Alignment X X F--SGGNTHIYMNHVEQCKEILRREPKELCELVISGLPYKFRYLSTKE-QLK-Y : :: : : : : : ::::: :: GDFIHTLGDAHIYLNHIEPLKIQLQREPRPFPKLRILRKVEKIDDFKAEDFQIEGYN X X

12 Sequence Alignment and Typical Scoring Function X X F--SGGNTHIYMNHVEQCKEILRREPKELCELVISGLPYKFRYLSTKE-QLK-Y : :: : : : : : ::::: :: GDFIHTLGDAHIYLNHIEPLKIQLQREPRPFPKLRILRKVEKIDDFKAEDFQIEGYN X X Region End Score = Similarity-weights - Penalties Region Start where: Region End Region Start Penalty = Gap-penalty + Size-of-gap x Gap-size-penalty

13 .. Sequence Similarity vs Evolutionary Distance Mutations Introduced per 100 Residues 0

14 Dayhoff s Acceptable Point Mutations Ala A Arg R 30 Asn N Asp D Cys C Gln Q Glu E Gly G His H Ile I Leu L Lys K Met M Phe F Pro P Ser S Thr T Trp W Tyr Y Val V A R N D C Q E G H I L K M F P S T W Y V Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val

15 Dayhoff s PAM 250 Matrix (Log-Odds Form) A Ala.18 R Arg N Asn D Asp C Cys Q Gln E Glu G Gly H His I Ile L Leu K Lys M Met F Phe P Pro S Ser T Thr W Trp Y Tyr V Val A R N D C Q E G H I L K M F P S T W Y V Ala Arg Asn Asp Cys Gln Glu Gly His Ile Leu Lys Met Phe Pro Ser Thr Trp Tyr Val

16 Mutation Data Matrix (MDM-78) Cys C 12 Ser S 0 2 Thr T Pro P Ala A Gly G Asn N Asp D Glu E Gln Q His H Arg R Lys K Met M Ile I Leu L Val V Phe F Tyr Y Trp W C S T P A G N D E Q H R K M I L V F Y W

17 Comparison of Scoring Matrices Sequences Compared Unitary Matrix Genetic Code Matrix Amino Acid Matrix PAM 250 Matrix Antibacterial substance A Streptomyces vs. Neocarzinostatin Streptomyces Ferredoxin Clostridium vs Ferredoxin Spirulina Hemoglobin Human vs. Myoglobin Human Hemoglobin Human vs. Globin CTT-III Midge Cytochrome C Horse vs. Cytochrome C6 Spirulina Cytochrome C Horse vs. Cytochrome C553 Desulfovibrio microglobulin Human vs. IG Human chain C4 region Ig chain C4 region Human vs. Ig chain C4 Human

18 Significance of Alignments vs PAMs

19 Detecting Evolutionary Relationships 300 million years 200 million years 100 years million Today PAM100 PAM100 PAM 100 PAM 100 PAM 200 PAM 150

20 Block Signatures for a Protein Family ( (After Henikoff and Henikoff) INKHIQ VSRVVN ASRALM VSHVIN VSAILN IRRDLN THVRVE GSSELA MTRGSN VGRILK LSHLFR LAHLFR ISRLLG LHRLFK HSGEQLAETLGMSRAAINKHIQ VTLYDVAEYAGVSYQTVSRVVN AMIKDVALKAKVSTATVSRALM ATIKDVAKRAGVSTTTVSHVIN ITIYDLAELSGVSASAVSAILN LHLKDAAALLGVSEMTIRRDLN TAYAELAKQFGVSPGTIHVRVE GSLTEAAHLLGTSQPTVSRELA MSQRELKNELGAGIATITRGSN ITRQEIGQIVGCSRETVGRILK FDIASVAQHVCLSPSRLSHLFR LRIDEVARHVCLSPSRLAHLFR MTRGDIGNYLGLTVETISRLLG VTLEALADQVGMSPFHLHRLFK SRAAINKHIVA VSYQTVSRVVN VSTATVSRALA GVTTTVSHVIN SGVSAVSAILN GVSEMTRRDLN TAYATIHVRVE GSQPTVSRELA MSIATITRGSN ISRETVGRILK FDISRLSHLFR LRPSRLAHLFR MTVETISRLLG TLEFHLHRLFK

21 Smith-Waterman Similarity Search Query: HU-NS1 Maximal Score: 452 PAM Matrix: 200 Gap Penalty: 5 Gap Extension: 0.5 No. Score Match Length DB ID Description Pred. No DBHB_ECOLI DNA-BINDING PROTEIN H 8.74e DBHB_SALTY DNA-BINDING PROTEIN H 1.54e DBHA_ECOLI DNA-BINDING PROTEIN H 1.64e DBHA_SALTY DNA-BINDING PROTEIN H 1.64e DBH_BACST DNA-BINDING PROTEIN I 1.35e DBH_BACSU DNA-BINDING PROTEIN I 1.35e DBH_VIBPR DNA-BINDING PROTEIN H 2.35e DBH_PSEAE DNA-BINDING PROTEIN H 2.14e DBH1_RHILE DNA-BINDING PROTEIN H 1.47e DBH_CLOPA DNA-BINDING PROTEIN H 2.52e DBH_RHIME DNA-BINDING PROTEIN H 3.18e DBH5_RHILE DNA-BINDING PROTEIN H 9.29e DBH_ANASP DNA-BINDING PROTEIN H 3.32e DBH_CRYPH DNA-BINDING PROTEIN H 2.70e DBH_THETH DNA-BINDING PROTEIN I 1.07e IHFA_SERMA INTEGRATION HOST FACT 4.46e IHFA_RHOCA INTEGRATION HOST FACT 3.52e IHFA_SALTY INTEGRATION HOST FACT 5.90e IHFA_ECOLI INTEGRATION HOST FACT 9.87e IHFB_ECOLI INTEGRATION HOST FACT 7.71e IHFB_SERMA INTEGRATION HOST FACT 7.71e TF1_BPSP1 TRANSCRIPTION FACTOR 3.42e DBH_THEAC DNA-BINDING PROTEIN H 2.12e GLGA_ECOLI GLYCOGEN SYNTHASE (EC 3.80e-01

22 GAPPED BLAST Starts with a Two Hit Approach

23 GAPPED BLAST Extension of Two Hit HSP

24 GAPPED BLAST Alignment

25 Decypher Search Engine [ decypher.stanford.edu/]

26 Decypher Database Search Engine (

27 Extreme Value Distribution of Scores

28 Expectation of Extreme Values r r ob(s > X) 1 exp{ Ke X } i =1 here r j =1 is the root of the equation: p i p j exp { s ij } = 1 p i and p j are the probabilities of each esidue in each sequence, ij are the similarity scores of wo residues. f the expected value of he scores for random sequences is 0, i. e. r r p i p j s ij < 0 i =1 j =1 hen there are two solutions for, ero and one other positive root Distribution of Scores > S Score S

29 . Dynamic Programming Query Database G L I V S R A D G I R E M T S P L K S G F V G V I L S K A E G I R D V S T

30 Generalized Dynamic Programming Database Query A R N D C Q E G H I L K M F P S T W Y V ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) ( ) G L I V S R A D G I R E M T S P L K S G F V

31 Profiles & Hidden Markov Models ( D 2 D 3 D 4 D 5 I 1 I 2 I 3 I 4 I 5 AA1 AA2 AA3 AA4 AA5 AA6

32 Discovering Function from Protein Sequence BLOCK, Weight Matrix or Position Specific Scoring Matrix Position A R N D C Q E G H I L K M F P S T W Y V Consensus Sequences Zinc Finger (C2H2 type) C.{2,4} C.{12} H.{3,5} H Sequences of Common Structure or Function Sequence Alignments VLSPADKTNVKAAWGKVGAHAGEYGAEALERMFLSFPTTKTYFPHF------DLSHGS : : : : : : : : : : : 2 HLTPEEKSAVTALWGKV--NVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGN AA1 Profiles, PSI-BLAST Hidden Markov Models D 2 I 1 I 2 I 3 I 4 I 5 AA2 D 3 AA3 D 4 AA4 D 5 AA5 AA6

33 Hidden Markov Models (after Haussler) D 2 D 3 D 4 D 5 I 1 I 2 I 3 I 4 I 5 AA1 AA2 AA3 AA4 AA5 AA6

34 Globin HMM Model

35 Decypher Database Search Engine (

36 General DNA Similarity Search Principles Search both Strands Translate ORFs Use most sensitive search possible BLAST for infinite gap penalty Smith Waterman for cdna/genome comparisons cdna =>Zero gap-length penalty Consider transition matrices Ensure that expected value of score is negative Examine results with exp.. between 0.05 and 10 Reevaluate results of borderline significance using limited query Beware of long results Limit query length to 1,000 bases Segment query if 1,000 bases

37 General Protein Similarity Search Principles Chose between local or global search algorithm Use most sensitive search algorithm available Original BLAST for no gaps Smith-Waterman for most flexibility Gapped BLAST for well delimited regions PSI-BLAST for families Initially BLOSUM62 and default gap penalties If no significant results, use BLOSUM30 and lower gap penalties Ensure expected score is negative Examine results between exp and 10 for biological significance Beware of long hits or those with unusual amino acid composition Reevaluate results of borderline significance using limited query Segment long queries 300 amino acids Segments around known motifs

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